sits_gam: Create temporal patterns using a generalised additive model...

In luizassis/sits: Satellite Image Time Series Analysis

Description

This function takes a set of time series samples as input estimates a set of patterns. The patterns are calculated based in a GAM model. The idea is to use a formula of type y ~ s(x), where x is a temporal reference and y if the value of the signal. For each time, there will be as many predictions as there are sample values. The GAM model predicts a suitable approximation that fits the assumptions of the statistical model. By default, the gam methods produces an approximation based on a smooth function.

This method is based on the "createPatterns" method of the dtwSat package, which is also described in the reference paper.

Usage

sits_gam(data.tb = NULL, bands = NULL, from = NULL, to = NULL,
  freq = 8, formula = y ~ s(x), ...)

Arguments

data.tb	a table in SITS format with time series to be classified using TWTDW
bands	the bands used to obtain the pattern
from	starting date of the estimate (month-day)
to	end data of the estimated (month-day)
freq	int - the interval in days for the estimates to be generated
formula	the formula to be applied in the estimate
...	any additional parameters

Value

patterns.tb a SITS table with the patterns

Author(s)

Victor Maus, [e-mail]

Gilberto Camara, [e-mail]

Rolf Simoes, [e-mail]

References

Maus V, Camara G, Cartaxo R, Sanchez A, Ramos FM, de Queiroz GR (2016). A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(8):3729-3739, August 2016. ISSN 1939-1404. doi:10.1109/JSTARS.2016.2517118.

luizassis/sits documentation built on May 30, 2019, 7:15 p.m.